Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles

Abstract

Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome.

Oncology and Pharmacogenomics Insights in Polycystic Ovary Syndrome: An Integrative Analysis

“…The initial exploration of the PRG performed in g:Profiler showed that the most relevant GO:biological processes were response to endogenous stimulus, organic subtract, and hormones as reported previously from 287 DEG in six PCOS data sets ( 45 ). In a group of upregulated genes detected in adipose tissue from women with PCOS, the term cell proliferation was enriched similarly as seen in this review report ( 39 ).…”

“…In a survival analysis, after examining PCOS differentially expressed genes (DEG) in patients with ovarian serous cystadenocarcinoma, a correlation with disease-free survival and overall survival was found. This finding highlighted the critical role of these genes in PCOS and its long term complications, particularly in OC ( 45 ). Even in pathway enrichment analysis of differentially methylated genes participating in a protein-protein interaction network, pathways associated with cancer, chronic myeloid leukemia, and prostate cancer were mainly enriched ( 46 ).…”

Establishment and Analysis of a Combined Diagnostic Model of Polycystic Ovary Syndrome with Random Forest and Artificial Neural Network

“…GO enrichment analysis was performed and displayed by bar plot and bubble plot. Among the 11 enriched GO terms, 4 terms including actin binding [ 41 ], myofibril [ 42 ], sarcomere [ 42 ], and contractile fiber part [ 42 ] were also identified in other PCOS researches. We listed the top 12 core genes screened by the RF model for classification in DEGs based on MeanDecreaseGini.…”

Protein Network Studies on PCOS Biomarkers With S100A8, Druggability Assessment, and RNA Aptamer Designing to Control Its Cyst Migration Effect

“…5 , a dataset repository (Oughtred et al, 2019), and the molecular interaction network was constructed in STRING Database (Szklarczyk et al, 2019). Biomarkers specific to PCOS and cancer cell invasion are retrieved from the recent research articles (Daan et al, 2016;Lu et al, 2017;Gerashchenko et al, 2019) and are used to construct another network. Both the networks were merged to find the first shell interactors of S100A8.…”